Boosting Data Quality

Boosting Data Quality - Application Development Trends - 1...

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Application Development Trends - http://www.adtmag.com/print.aspx?id=6321 1 of 5 7/28/2006 10:06 AM Data Warehousing Special Report: Data quality and the bottom line 5/1/2002 By Wayne W. Eckerson During the past 50 years, the developed world has moved from an industrial economy to an information economy. Companies now compete on their ability to absorb and respond to information, not just manufacture and distribute products. Intellectual capital and know-how are more important assets than physical infrastructure and equipment. If information is the currency of the new economy, then data is a critical raw material needed for success. Just as a refinery takes crude oil and transforms it into numerous petroleum products, companies use data to generate a multiplicity of information assets. These assets form the basis of the strategic plans and actions that determine a firm's success. Consequently, poor quality data can have a negative impact on the health of a company. If not identified and corrected early on, defective data can contaminate all downstream systems and information assets. The problem with data is that its quality quickly degenerates over time. Experts say 2% of records in a customer file become obsolete in a month because customers die, divorce, marry and move. In addition, data-entry errors, systems migrations and changes to source systems, among other things, generate bucketloads of errors. As well, as organizations fragment into different divisions and units, interpretations of data elements mutate to meet local business needs. A data element that one individual finds valuable may be nonsense to an individual in a different group. The Data Warehousing Institute (TDWI) estimates that poor quality customer data costs U.S. businesses a staggering $611 billion a year in postage, printing and staff overhead (TDWI estimates based on cost-savings cited by survey respondents and others who have cleaned up name and address Frighteningly, the real cost of poor quality data is much higher. Organizations can frustrate and alienate loyal customers by incorrectly addressing letters or failing to recognize them when they call, or visit a store or Web site. Once a company loses its loyal customers, it loses its base of sales and referrals, as well as future revenue potential. Given the business impact of poor quality data, it is bewildering to see the casual way in which most companies manage this critical resource. Most companies do not fund programs designed to build quality into their data in a proactive, systematic and sustained manner. According to TDWI's Data Quality Survey, almost half of all firms have no plan for managing data quality. Part of the problem is that most organizations overestimate the quality of their data and underestimate
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